English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

To solve the problem that self-alignment accuracy of platform inertial navigation system will be affected a lot under significant interference, an adaptive blind source separation algorithm based on wavelet – EEMD method is proposed. This method use wavelet decomposition to remove the high frequency signal, and then the EEMD can be used to decompose the target signal. While using wavelet decomposition, an algorithm that using volatility to determine the decomposition layers is proposed, and this method increased the adaptability of wavelet decomposition algorithm. Finally, experiment data validation and some compare are carried on to confirm the proposed method, and the results show that the method has a great advantage, and it can extract the target signals from the disturbed data under significantly interference and greatly improve the alignment accuracy of platform inertial navigation system.

Platform Angle Signal Blind Source Separation Algorithm Based on Wavelet –EEMD Method